Sunday, September 12, 2010

Just saw this polished-turd marketing-speak on the Giant Bicycles website. How difficult would it really have been to say, "This bike in size medium weighs 24.8lbs in factory-configuration"? Instead, we get this crap:

"How much does this bike weigh? It’s a common question, and rightly so. But the truth is, there are no industry standards for claiming bike weights—and this leads to a lot of misinformation. Variances exist based on size, frame material, finish and hardware. And as bikes get lighter, these differences become more critical. At Giant, we believe the only way to truly know the weight of any particular bike is to find out for yourself at your local retailer."

6 comments:

Good point. How hard is it for them to weigh the bike as it comes from the factory. Yes, if I put a different saddle on it, some pedals, a seat bag with extra tube, leavers, CO2, and a chuck, then it will weigh more. I hate PR and the flacks that write the dreck.

How hard could it be? Just tell us the weight of a medium frame and we can, just about, figure it out for ourselves. Or, we could go to our 'local' retailer and find a 'qualified technician' who can just regurgitate the same gobshite from the Giant brochure, before (scientifically and with unerring accuracy) allow us to pick one up (regardless of size) and give it a bit of a shake....

The Anthem is a great bike though, so don’t let Giant’s marketing people put you off too much! Mind you, have you read some of the other manufacturers stuff??? I think it’s all about lifestyle….

Specialized provides a similar response when asking about the weight of their bikes. Interestingly, the folks at Scott Bikes have no problem displaying the bike weights on their website...2010 Spark RC weighs in at a sick 21.59lbs!!

In probability theory and statistics, the variance is used as one of several descriptors of a distribution. It describes how far values lie from the mean. In particular, the variance is one of the moments of a distribution. In that context, it forms part of a systematic approach to distinguishing between probability distributions. While other such approaches have been developed, those based on moments are advantageous in terms of mathematical and computational simplicity.

The variance is a parameter describing a theoretical probability distribution, while a sample of data from such a distribution can be used to construct an estimate of this variance: in the simplest cases this estimate can be the sample variance.

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